Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced activity, selectivity, and safety.


Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by Reaxense.


The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.


Our high-tech, dedicated method is applied to construct targeted libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of biological functions.


Our library stands out due to several important features:


  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.

  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.

  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.

  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
Q9H4M9

UPID:
EHD1_HUMAN

ALTERNATIVE NAMES:
PAST homolog 1; Testilin

ALTERNATIVE UPACC:
Q9H4M9; O14611; Q2M3Q4; Q9UNR3

BACKGROUND:
The EH domain-containing protein 1, known alternatively as PAST homolog 1 or Testilin, is integral to cellular processes such as membrane reorganization, vesiculation of endocytic membranes, and membrane trafficking. Its recruitment to endosomal membranes is crucial for nerve growth factor-stimulated neurite outgrowth and myoblast fusion. The protein's involvement in the retrograde dendritic transport of BACE1 and sorting to axons underscores its significance in neuronal APP processing. Furthermore, it plays a vital role in cilium biogenesis, particularly in the early steps of forming the ciliary vesicle, by recruiting essential proteins and components for membrane extension.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of EH domain-containing protein 1 could open doors to potential therapeutic strategies.

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